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Building Solid Go GraphQL Applications Quickly

After numerous successful deployments of Go GraphQL applications a repeatable building methodology has emerged. Two of the most significant contributing factors to the successful development and deployment of those projects are a good GraphQL server package to build the application and suitable black box testing tool.

Black Box Testing

It would be hard to argue that application level black box testing is not the gold standard for testing. Sure, unit testing is important but the final gate before release or deployment really should be tests that validate behavior as the end users will see it.

GraphQL servers are no exception to the black box testing rule. A test suite that exercises an GraphQL application using the same HTTP API that end users will use make it less likely there will be surprises after deployment. A black box test suite is also ideal for continuous integration tests on merges during development.

With the proper tooling, testing through the HTTP API of a GraphQL application is often easier than trying to piece together regression tests that only exercise internal APIs. An effective tool should be able to play the role of a user. GraphQL-Test-Tool is such a tool. GTT for short, GraphQL-Test-Tool is a script driven test tool for testing GraphQL applications. I addition to providing repeatable regression tests and CI, GTT scripts end up being great examples for end users.

GTT is written in Go but can be used for testing any GraphQL server that has an HTTP API. The example this article describes demonstrates the use of GTT as a test tool for a Go application test as well as a Ruby server that implements the same schema. This article focuses on the Go test setup.

Application

The GraphQL application is this example is taken from the GGql reflection example. A few changes to the example so that more of the GTT features could be explained but basically it is the same. GGql is the fastest Go GraphQL server as well as the easiest to use as shown by this comparison. The README.md for the GGql example explains the basics of the application so that will not be duplicated here.

A GGql root object is able to return the formatted schema that it is serving. By adding an HTTP handler to /graphql/schema an HTTP request can be made to respond with the full schema in SDL format.

	http.HandleFunc("/graphql/schema", func(w http.ResponseWriter, r *http.Request) {
		q := r.URL.Query()
		full := strings.EqualFold(q.Get("full"), "true")
		desc := strings.EqualFold(q.Get("desc"), "true")
		sdl := root.SDL(full, desc)
		_, _ = w.Write([]byte(sdl))
	})

Another addition was of a setLike() mutation field. Since we are using the GGql reflection approach to resolving fields all that has to be done is add the Mutation function and GGql takes care of the rest.

func (m *Mutation) SetLike(artist, song string, count int64) *Song {
	if a := m.query.Artist(artist); a != nil {
		if s := a.Song(song); s != nil {
			s.Likes = int(count)
			return s
		}
	}
	return nil
}

The GGql example did not include support for passing in variable nor the operation name as query parameters in the URL. That functionality was also added with these lines in the handleGraphQL() function.

	var vars map[string]interface{}
	if variables, err := oj.ParseString(req.URL.Query().Get("variables")); err == nil {
		vars, _ = variables.(map[string]interface{})
	}
	op := req.URL.Query().Get("operationName")

With the application ready for testing lets move on to the test setup.

Test Setup

There are two choices when setting up the tests for an application. One is to use the full application for a true black box test and the other is to split the application into a command (cmd) portion and a package portion so that the package code can be tested in the same process space as the test code. There are advantages and disadvantages to each.

True Black Box

A true black box approach runs the application completely separate from the test code. This had the advantage of being able to test a server implemented in any language. The disadvantage is that the Go test coverage tools will not work. Running as a separate process also means debugging print statements are a little more difficult to display.

Embedded Tests

In order to run the application in the same code space as the test code the application needs to be callable from the test code. To do that a package with the application in it needs to be imported. Thats not difficult to do. Just create a cmd directory and put a light weight main() function in an application directory of the cmd directory that calls the package where all the rest of the code resides. Go coverage tools then work and debug print statements show up as the tests are running. The downside to an embedded configuration is that the server has to be written in Go and separated in a cmd and package directory. Of course writing the application in Go isn't really much of a downside.

Implementation

The true black box testing approach is more applicable to a wider audience and has a certain testing purity to it so that is the approach described here. Jumping right in, the test scripts are placed in a gtt subdirectory to keep files organized. They can be placed anywhere though.

While not necessary, the application will be started just once and then each test will be executed against the running app. The code to run the application is in main_test.go while the test functions for running the individual tests are in song_test.go.

main_test.go

Since the tests can not be run without first starting the application it will be necessary to create a TestMain() function. TestMain() begins with setting up a flag to determine if the Go or Ruby version of the application will be called. Next the run() function is called. The run() function will do most of the work and return an error if anything goes wrong with the setup or if the tests fail.

func TestMain(m *testing.M) {
	flag.BoolVar(&ruby, "ruby", ruby, "run the ruby server instead of go server")
	flag.Parse()

	if err := run(m); err != nil {
		fmt.Println(err.Error())
		os.Exit(1)
	}
	os.Exit(0)
}

The run() function first finds a free port to run the application on. This avoids accidental collisions with other servers or with previously tests that may be taking longer to shutdown than expected.

func run(m *testing.M) (err error) {
	var addr *net.TCPAddr
	if addr, err = net.ResolveTCPAddr("tcp", "localhost:0"); err == nil {
		var ln *net.TCPListener
		if ln, err = net.ListenTCP("tcp", addr); err == nil {
			testPort = ln.Addr().(*net.TCPAddr).Port
			ln.Close()
		}
		if err != nil {
			return
		}
	}

With a free port identified, the application is started. Since we want to collect the output from the exec.Cmd we grab the application stdout before calling start().

	var cmd *exec.Cmd
	if ruby {
		cmd = exec.Command("ruby", "song.rb", "-p", strconv.Itoa(testPort))
	} else {
		cmd = exec.Command("go", "run", "main.go", "-p", strconv.Itoa(testPort))
	}
	stdout, _ := cmd.StdoutPipe()
	if err = cmd.Start(); err != nil {
		return
	}

A go routine running concurrently will have to read the stdout while the application is running. The buffer size of stdout is limited so if the application generates too much output the application will hang attempting to write to stdout. By reading concurrently the ioutil.ReadAll() buffer will expand and collect all the output. After stdout is closed ioutil.ReadAll() will return but the main thread needs to be told it is free to continue and print the collected output. The done chan takes care of that.

	var out []byte
	done := make(chan bool)
	go func() {
		out, _ = ioutil.ReadAll(stdout)
		done <- true
	}()

The tests shouldn't be run until the application has started or else the tests will fail to connect to the application. A simple sleep could be used then that forces a slowdown of the test. It's better to continue immediately once the application is up and accepting requests. A loop with a delay between attempts takes care of that.

	for i := 0; i < 25; i++ {
		u := fmt.Sprintf("http://localhost:%d", testPort)
		var r *http.Response
		if r, err = http.Get(u); err == nil {
			r.Body.Close()
			break
		}
		time.Sleep(time.Millisecond * 200)
	}

If there were no errors connecting to the application the tests can be run.

	if err == nil && 0 != m.Run() {
		err = fmt.Errorf("tests failed")
	}
}

After the tests finish it's time to clean up by killing the application and printing the application output. Note the wait on the done chan before proceeding to printing to make sure all the output has been collected.

	if cmd.Process != nil {
		_ = cmd.Process.Kill()
	}
	stdout.Close()
	<-done
	if testing.Verbose() {
		fmt.Println(string(out))
	}

song_test.go

Individual tests all follow the same pattern so keeping with the DRY principle, a common gttTest() function is used for all the GTT tests. The only variable in the GTT tests is the script file to be executed so that is passed as an argument to the gttTest() function. A GTT UseCase is created with the filepath followed by the creation of a gtt.Runner with the server information. The final step is to tell the Runner to Run.

func gttTest(t *testing.T, filepath string) {
	uc, err := gtt.NewUseCase(filepath)
	if err != nil {
		t.Fatal(err.Error())
	}
	r := gtt.Runner{
		Server:   fmt.Sprintf("http://localhost:%d", testPort),
		Base:     "/graphql",
		Indent:   2,
		UseCases: []*gtt.UseCase{uc},
	}
	if testing.Verbose() {
		r.ShowComments = true
		r.ShowResponses = true
		r.ShowRequests = true
	}
	if err = r.Run(); err != nil {
		t.Fatal(err.Error())
	}
}

Each test is set up to run in a separate test function. This allows selecting individual tests from the command line with the go test -run option. The tests themselves just call the gttTest() function with the appropriate script file name.

func TestTypes(t *testing.T) {
	gttTest(t, "gtt/types.json")
}

All the interactions with the server are in the script file.

Test Scripts

Script files are in a separate directory named gtt. More details about the structure of the script files can be found in file_format.md.

Lets look at a few of the features available in GTT by touching on a few of of the scripts.

  • comments - Comments in the script file are useful if using the scripts to also document use cases. Comments can be a single string value for a comment key as in types.json or multiple lines in an array as in artist_names_get.json.

  • sortBy - Order is often important in arrays yet at times order may be be random depending on the data source that returns a list of items. The sortBy option will sort output before comparing to the expected. artist_names_get.json is an example of using the sortBy option.

  • method - Switching between HTTP methods, either GET or POST is as simple as either providing a content element or not as seen in artist_names_get.json and artist_names_post.json.

  • remember - Sometimes the result of one step is needed in a subsequent step. The remember and vars elements provide that functionality in top.json.

  • lazy - GTT is extremely tolerant of script format and supports the SEN (Simple Encoding Notation). The relaxed format is used in top.json but it also allow for JSON with errors such as missing commas or extra commas.

Summary

With a full set of use cases a GraphQL application can be deployed with confidence. Having the ability to run regression tests after making changes saves time especially when a hot fix is needed. A much appreciated feature of scripted tests is that users have examples they can use when putting together we front ends.